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The land ice contribution to global mean sea level rise has not yet been predicted1 using ice sheet and glacier models for the latest set of socio-economic scenarios, nor using coordinated exploration of uncertainties arising from the various computer models involved. Two recent international projects generated a large suite of projections using multiple models2-8, but primarily used previous-generation scenarios9 and climate models10, and could not fully explore known uncertainties. Here we estimate probability distributions for these projections under the new scenarios11,12 using statistical emulation of the ice sheet and glacier models. We find that limiting global warming to 1.5 degrees Celsius would halve the land ice contribution to twenty-first-century sea level rise, relative to current emissions pledges. The median decreases from 25 to 13 centimetres sea level equivalent (SLE) by 2100, with glaciers responsible for half the sea level contribution. The projected Antarctic contribution does not show a clear response to the emissions scenario, owing to uncertainties in the competing processes of increasing ice loss and snowfall accumulation in a warming climate. However, under risk-averse (pessimistic) assumptions, Antarctic ice loss could be five times higher, increasing the median land ice contribution to 42 centimetres SLE under current policies and pledges, with the 95th percentile projection exceeding half a metre even under 1.5 degrees Celsius warming. This would severely limit the possibility of mitigating future coastal flooding. Given this large range (between 13 centimetres SLE using the main projections under 1.5 degrees Celsius warming and 42 centimetres SLE using risk-averse projections under current pledges), adaptation planning for twenty-first-century sea level rise must account for a factor-of-three uncertainty in the land ice contribution until climate policies and the Antarctic response are further constrained.

Glaciers are present in many large river basins, and due to climate change, they are undergoing considerable changes in terms of area, volume, magnitude and seasonality of runoff. Although the spatial extent of glaciers is very limited in most large river basins, their role in hydrology can be substantial because glaciers store large amounts of water at varying timescales. Large-scale hydrological models are an important tool to assess climate change impacts on water resources in large river basins worldwide. Nevertheless, glaciers remain poorly represented in large-scale hydrological models. Here we present a coupling between the large-scale glacier model Open Global Glacier Model (OGGM) v1.5.3 and the large-scale hydrological model Community Water Model (CWatM) V1.08. We evaluated the improved glacier representation in the coupled model against the baseline hydrological model for four selected river basins at 5 arcmin resolution and globally at 30 arcmin resolution, focusing on future discharge projections under low- and high-emission scenarios. We find that increases in future discharge are attenuated, whereas decreases are exacerbated when glaciers are represented explicitly in the large-scale hydrological model simulations. This is explained by a projected decrease in glacier-sourced runoff in almost all basins. Calibration can compensate for lacking glacier representation in large-scale hydrological models in the past. Nevertheless, only an improved glacier representation can prevent underestimating future discharge changes, even far downstream at the outlets of large glacierized river basins. Therefore, incorporating a glacier representation into large-scale hydrological models is important for climate change impact studies, particularly when focusing on summer months or extreme years. The uncertainties in glacier-sourced runoff associated with inaccurate precipitation inputs require the continued attention and collaboration of glacier and hydrological modelling communities. [ABSTRACT FROM AUTHOR]

High Asia has experienced strong environmental changes in recent decades, as evident in records of glaciers, lakes, tree rings, and vegetation. The multiscale understanding of the climatic drivers, however, is still incomplete. In particular, few systematic assessments have evaluated to what degree, if at all, the midlatitude westerly circulation modifies local surface climates in the reach of the Indian Summer Monsoon. This paper shows that a southward shift of the upper-tropospheric westerlies contributes significantly to climate variability in the core monsoon season (July–September) by two prominent dipole patterns at the surface: cooling in the west of High Asia contrasts with warming in the east, while moist anomalies in the east and northwest occur with drying along the southwestern margins. Circulation anomalies help to understand the dipoles and coincide with shifts in both the westerly wave train and the South Asian High, which imprint on air mass advection and local energy budgets. The relation of the variabilities to a well-established index of midlatitude climate dynamics allows future research on climate proxies to include a fresh hypothesis for the interpretation of environmental changes.

Knowledge of the ice thickness distribution of glaciers and ice caps is an important prerequisite for many glaciological and hydrological investigations. A wealth of approaches has recently been presented for inferring ice thickness from characteristics of the surface. With the Ice Thickness Models Intercomparison eXperiment (ITMIX) we performed the first coordinated assessment quantifying individual model performance. A set of 17 different models showed that individual ice thickness estimates can differ considerably - locally by a spread comparable to the observed thickness. Averaging the results of multiple models, however, significantly improved the results: on average over the 21 considered test cases, comparison against direct ice thickness measurements revealed deviations on the order of 10 ± 24% of the mean ice thickness (1σ estimate). Models relying on multiple data sets - such as surface ice velocity fields, surface mass balance, or rates of ice thickness change - showed high sensitivity to input data quality. Together with the requirement of being able to handle large regions in an automated fashion, the capacity of better accounting for uncertainties in the input data will be a key for an improved next generation of ice thickness estimation approaches.

Avalanches are important contributors to the mass balance of glaciers located in mountain ranges with steep topographies. Avalanches result in localized over-accumulation that is seldom accounted for in glacier models due to the difficulty of quantifying this contribution, let alone the occurrence of avalanches in these remote regions. Here, we developed an approach to semi-automatically map avalanche deposits over long time periods and at scales of multiple glaciers, utilizing imagery from Sentinel-1 synthetic aperture radar (SAR). This approach performs particularly well for scenes acquired in winter and in the morning but can also be used to identify avalanche events throughout the year. We applied this method to map 16 302 avalanche deposits over a period of 5 years at a 6 to 12 d interval over the Mt Blanc massif (European Alps), the Everest (central Himalaya) region, and the Hispar (Karakoram) region. These three survey areas are all characterized by steep mountain slopes but also present contrasting climatic characteristics. Our results enable the identification of avalanche hotspots on these glaciers and allow us to quantify the avalanche activity and its spatio-temporal variability across the three regions. The avalanche deposits are preferentially located at lower elevations relative to the hypsometry of the glacierized catchments and are also constrained to a smaller elevation range at the Asian sites, where they have a limited influence on their extensive debris-covered tongues. Avalanche events coincide with solid precipitation events, which explains the high avalanche activity in winter in the Mt Blanc massif and during the monsoon in the Everest region. However, there is also a time lag of 1–2 months, visible especially in the Everest region, between the precipitation and avalanche events, indicative of some snow retention on the mountain headwalls. This study therefore provides critical insights into these mass redistribution processes and tools to account for their influence on glacier mass balance. [ABSTRACT FROM AUTHOR]

We present the first study using decadal re-forecasts to simulate global glacier climatic mass balance, bridging the gap between seasonal and long-term simulation of glacier contribution to catchment hydrology and sea level rise. Using the Open Global Glacier Model, driven by Coupled Model Intercomparison Project 6 ensembles of initialised decadal climate re-forecasts of temperature and precipitation, we demonstrate the skill of glacier mass balance re-forecasts on the decadal timescale, for respectively 279 reference glaciers and all land-terminating glaciers globally. For comparison, the glacier model is also forced with a simple persistence forecast and general circulation model historical time series and projections, representing the current state of the art. The results from forcing with decadal re-forecasts provide improvement over the other two methods. Simulating single years, especially at short lead times, decadal re-forecasts show the highest Pearson correlations and lowest mean absolute errors, compared to observed mass balance. Simulating cumulative mass balance over full decades for the 279 reference glaciers, forcing with decadal re-forecasts yields a decrease in mean absolute error of 18 % and 16 % compared to forcing with persistence forecasts and historical global circulation model simulations, respectively. Globally, comparing average mass balance over the time period 2000–2020, forcing with decadal re-forecasts results in the highest number of regions with 'good fit' to observations (difference from observed regional mass balance =< 0.1 m w.e.), compared to the persistence and historical climate model forcing. These findings indicate that the use of decadal predictions for glacier modelling is operationally feasible and holds significant potential for future hydrological applications. [ABSTRACT FROM AUTHOR]

Geoscientific models are facing increasing challenges to exploit growing datasets coming from remote sensing. Universal differential equations (UDEs), aided by differentiable programming, provide a new scientific modelling paradigm enabling both complex functional inversions to potentially discover new physical laws and data assimilation from heterogeneous and sparse observations. We demonstrate an application of UDEs as a proof of concept to learn the creep component of ice flow, i.e. a nonlinear diffusivity differential equation, of a glacier evolution model. By combining a mechanistic model based on a two-dimensional shallow-ice approximation partial differential equation with an embedded neural network, i.e. a UDE, we can learn parts of an equation as nonlinear functions that then can be translated into mathematical expressions. We implemented this modelling framework as ODINN.jl, a package in the Julia programming language, providing high performance, source-to-source automatic differentiation (AD) and seamless integration with tools and global datasets from the Open Global Glacier Model in Python. We demonstrate this concept for 17 different glaciers around the world, for which we successfully recover a prescribed artificial law describing ice creep variability by solving ∼ 500 000 ordinary differential equations in parallel. Furthermore, we investigate which are the best tools in the scientific machine learning ecosystem in Julia to differentiate and optimize large nonlinear diffusivity UDEs. This study represents a proof of concept for a new modelling framework aiming at discovering empirical laws for large-scale glacier processes, such as the variability in ice creep and basal sliding for ice flow, and new hybrid surface mass balance models. [ABSTRACT FROM AUTHOR]

Glaciers are retreating globally and are projected to continue to lose mass in the coming decades, directly affecting downstream ecosystems through changes in glacier runoff. Estimating the future evolution of glacier runoff involves several sources of uncertainty in the modelling chain, which to date have not been comprehensively assessed on a regional scale. In this study, we used the Open Global Glacier Model (OGGM) to estimate the glacier evolution of each glacier (area > 1 km2) in the Patagonian Andes (40–56° S), which together represent 82 % of the glacier area of the Andes. We used different glacier inventories (n = 2), ice thickness datasets (n = 2), historical climate datasets (n = 4), general circulation models (GCMs; n = 10), emission scenarios (SSPs; n = 4), and bias correction methods (BCMs; n = 3) to generate 1,920 possible scenarios over the period 1980–2099. For each scenario and catchment, glacier runoff and melt on glacier time series were characterized by ten glacio-hydrological signatures (i.e., metrics). We used the permutation feature importance of random forest regression models to assess the relative importance of each source on the signatures of each catchment. Considering all scenarios, 61 % ± 14 % of the catchment area (30 % ± 13 % of glacier area) has already peaked in terms of glacier melt (year 2020), and 43 % ± 8 % of the catchment area (18 % ± 7 % of glacier area) will lose more than 80 % of its volume this century. Considering the melt on glacier signatures, the future sources of uncertainty (GCMs, SSPs and BCMs) were the main source in only 18 % ± 21 % of the total catchment area. In contrast, the reference climate was the most important source in 78 % ± 21 % of the catchment area, highlighting the importance of the choices we make in the calibration procedure. The results provide a basis for prioritizing future efforts (e.g., improve reference climate characterization) to reduce glacio-hydrological modelling gaps in poorly instrumented regions, such as the Patagonian Andes. [ABSTRACT FROM AUTHOR]

Avalanches are important contributors to the mass balance of glaciers located in mountain ranges with steep topographies. They result in localised over-accumulation that is seldom accounted for in glacier models, due to the difficulty to quantify this contribution, let alone the occurrence of avalanches in these remote regions. Here, we developed an approach to semi-automatically map avalanche deposits over long time periods and at scales of multiple glaciers, utilising imagery from Sentinel-1 Synthetic Aperture Radar (SAR). This approach performs particularly well for scenes acquired in winter and in the morning, but can also be used to identify avalanche events throughout the year. We applied this method to map 16,302 avalanche deposits over a period of five years at a 6 to 12 days interval over the Mt Blanc massif (European Alps), the Everest (Central Himalaya) and Hispar (Karakoram) regions. These three survey areas are all characterised by steep mountain slopes, but also present contrasting climatic characteristics. Our results enable the identification of avalanche hotspots at the surface of these glaciers and allow us to quantify the avalanche activity and its spatio-temporal variability across the three regions. The avalanche deposits are preferentially located at lower elevations relative to the hypsometry of the glacierized catchments, and are also constrained to a smaller elevation range at the Asian sites, where they have a limited influence on their extensive debris-covered tongues. Avalanche events coincide with solid precipitation events, which explains the high avalanche activity in winter in the Mt Blanc massif and during the monsoon in the Everest region. However, there is also a time lag of 1–2 months, visible especially in the Everest region, between the precipitation and avalanche events, indicative of some snow retention on the mountain headwalls. Ultimately, this study provides critical insights into these mass redistribution processes as well as tools to account for their influence on glacier mass balance. [ABSTRACT FROM AUTHOR]

We revise and evaluate frontal ablation fluxes obtained by the Open Global Glacier Model (OGGM) for Greenland's tidewater peripheral glaciers de-coupled from the ice sheet. By making use of new region-wide ice thickness and solid ice discharge data, we re-evaluate model performance and suggest future research directions to improve the ice thickness estimation of glacier models. OGGM is unable to predict individual tidewater glacier dynamics well if it has to rely only on surface mass balance estimates and the assumption of a closed budget to constrain the calving parameterization. Velocity observations are essential to constrain the model and estimate the dynamic mass loss of Greenland's tidewater peripheral glaciers. [ABSTRACT FROM AUTHOR]